Antibiotics are widely used in very low-birth-weight infants (VLBW, <1500 g), and excess exposure, particularly to broad-spectrum antibiotics, is associated with significant morbidity. An antibiotic spectrum index (ASI) quantifies antibiotic exposure by relative antimicrobial activity, adding information to exposure measured by days of therapy (DOT). We compared ASI and DOT across multiple centers to evaluate differences in antibiotic exposures.

We extracted data from patients admitted to 3 level-4 NICUs for 2 years at 2 sites and for 1 year at a third site. We calculated the ASI per antibiotic days and DOT per patient days for all admitted VLBW infants <32 weeks gestational age. Clinical variables were compared as percentages or as days per 1,000 patient days. We used Kruskal-Wallis tests to compare continuous variables across the 3 sites.

Demographics were similar for the 734 VLBW infants included. The site with the highest DOT per patient days had the lowest ASI per antibiotic days and the site with the highest mortality and infection rates had the highest ASI per antibiotic days. Antibiotic utilization varied by center, particularly for choice of broad-spectrum coverage, although the organisms causing infection were similar.

An antibiotic spectrum index identified differences in prescribing practice patterns among 3 NICUs unique from those identified by standard antibiotic use metrics. Site differences in infection rates and unit practices or guidelines for prescribing antibiotics were reflected in the ASI. This comparison uncovered opportunities to improve antibiotic stewardship and demonstrates the utility of this metric for comparing antibiotic exposures among NICU populations.

An accurate estimate of the average number of hand hygiene opportunities per patient hour (HHO rate) is required to implement group electronic hand hygiene monitoring systems (GEHHMSs). We sought to identify predictors of HHOs to validate and implement a GEHHMS across a network of critical care units.

Multicenter, observational study (10 hospitals) followed by quality improvement intervention involving 24 critical care units across 12 hospitals in Ontario, Canada.

Critical care patient beds were randomized to receive 1 hour of continuous direct observation to determine the HHO rate. A Poisson regression model determined unit-level predictors of HHOs. Estimates of average HHO rates across different types of critical care units were derived and used to implement and evaluate use of GEHHMS.

During 2,812 hours of observation, we identified 25,417 HHOs. There was significant variability in HHO rate across critical care units. Time of day, day of the week, unit acuity, patient acuity, patient population and use of transmission-based precautions were significantly associated with HHO rate. Using unit-specific estimates of average HHO rate, aggregate HH adherence was 30.0% (1,084,329 of 3,614,908) at baseline with GEHHMS and improved to 38.5% (740,660 of 1,921,656) within 2 months of continuous feedback to units (P < .0001).

Unit-specific estimates based on known predictors of HHO rate enabled broad implementation of GEHHMS. Further longitudinal quality improvement efforts using this system are required to assess the impact of GEHHMS on both HH adherence and clinical outcomes within critically ill patient populations.

We analyzed 2017 healthcare facility-onset (HO) vancomycin-resistant Enterococcus (VRE) bacteremia data to identify hospital-level factors that were significant predictors of HO-VRE using the Centers for Disease Control and Prevention (CDC) National Healthcare Safety Network (NHSN) multidrug-resistant organism and Clostridioides difficile reporting module. A risk-adjusted model that can be used to calculate the number of predicted HO-VRE bacteremia events in a facility was developed, thus enabling the calculation of VRE standardized infection ratios (SIRs).

Acute-care hospitals reporting at least 1 month of 2017 VRE bacteremia data were included in the analysis. Various hospital-level characteristics were assessed to develop a best-fit model and subsequently derive the 2018 national and state SIRs.

In 2017, 470 facilities in 35 states participated in VRE bacteremia surveillance. Inpatient VRE community-onset prevalence rate, average length of patient stay, outpatient VRE community-onset prevalence rate, and presence of an oncology unit were all significantly associated (all 95% likelihood ratio confidence limits excluded the nominal value of zero) with HO-VRE bacteremia. The 2018 national SIR was 1.01 (95% CI, 0.93–1.09) with 577 HO bacteremia events reported.

The creation of an SIR enables national-, state-, and facility-level monitoring of VRE bacteremia while controlling for individual hospital-level factors. Hospitals can compare their VRE burden to a national benchmark to help them determine the effectiveness of infection prevention efforts over time.

To evaluate the role of procalcitonin (PCT) results in antibiotic decisions for COVID-19 patients at hospital presentation.

Multicenter retrospective observational study of patients ≥18 years hospitalized due to COVID-19 at the Johns Hopkins Health system. Patients who were transferred from another facility with >24 hours stay and patients who died within 48 hours of hospitalization were excluded.

Elevated PCT values were determined based on each hospital’s definition. Antibiotic therapy and PCT results were evaluated for patients with no evidence of bacterial community-acquired pneumonia (bCAP) and patients with confirmed, probable, or possible bCAP. The added value of PCT testing to clinical criteria in detecting bCAP was evaluated using receiving operating curve characteristics (ROC).

Of 962 patients, 611 (64%) received a PCT test. ROC curves for clinical criteria and clinical criteria plus PCT test were similar (at 0.5 ng/mL and 0.25 ng/mL). By bCAP group, median initial PCT values were 0.58 ng/mL (interquartile range [IQR], 0.24–1.14), 0.23 ng/mL (IQR, 0.1–0.63), and 0.15 ng/mL (IQR, 0.09–0.35) for proven/probable, possible, and no bCAP groups, respectively. Among patients without bCAP, an elevated PCT level was associated with 1.8 additional days of CAP therapy (95% CI, 1.01–2.75; P < .01) compared to patients with a negative PCT result after adjusting for potential confounders. Duration of CAP therapy was similar between patients without a PCT test ordered and a low PCT level for no bCAP and possible bCAP groups.

PCT results may be abnormal in COVID-19 patients without bCAP and may result in receipt of unnecessary antibiotics.

To study whether replacement of nosocomial ampicillin-resistant Enterococcus faecium (ARE) clones by vancomycin-resistant E. faecium (VRE), belonging to the same genetic lineages, increases mortality in patients with E. faecium bacteremia, and to evaluate whether any such increase is mediated by a delay in appropriate antibiotic therapy.

Retrospective, matched-cohort study.

The study included 20 Dutch and Danish hospitals from 2009 to 2014.

Within the study period, 63 patients with VRE bacteremia (36 Dutch and 27 Danish) were identified and subsequently matched to 234 patients with ARE bacteremia (130 Dutch and 104 Danish) for hospital, ward, length of hospital stay prior to bacteremia, and age. For all patients, 30-day mortality after bacteremia onset was assessed.

The risk ratio (RR) reflecting the impact of vancomycin resistance on 30-day mortality was estimated using Cox regression with further analytic control for confounding factors.

The 30-day mortality rates were 27% and 38% for ARE in the Netherlands and Denmark, respectively, and the 30-day mortality rates were 33% and 48% for VRE in these respective countries. The adjusted RR for 30-day mortality for VRE was 1.54 (95% confidence interval, 1.06–2.25). Although appropriate antibiotic therapy was initiated later for VRE than for ARE bacteremia, further analysis did not reveal mediation of the increased mortality risk.

Compared to ARE bacteremia, VRE bacteremia was associated with higher 30-day mortality. One explanation for this association would be increased virulence of VRE, although both phenotypes belong to the same well-characterized core genomic lineage. Alternatively, it may be the result of unmeasured confounding.

Patients admitted to the hospital may unknowingly carry severe acute respiratory coronavirus virus 2 (SARS-CoV-2), and hospitals have implemented SARS-CoV-2 admission screening. However, because SARS-CoV-2 reverse-transcription polymerase chain reaction (RT-PCR) assays may remain positive for months after infection, positive results may represent active or past infection. We determined the prevalence and infectiousness of patients who were admitted for reasons unrelated to COVID-19 but tested positive for SARS-CoV-2 on admission screening.

We conducted an observational study at the University of Iowa Hospitals & Clinics from July 7 to October 25, 2020. All patients admitted without suspicion of COVID-19 were included, and medical records of those with a positive admission screening test were reviewed. Infectiousness was determined using patient history, PCR cycle threshold (Ct) value, and serology.

In total, 5,913 patients were screened and admitted for reasons unrelated to COVID-19. Of these, 101 had positive admission RT-PCR results; 36 of these patients were excluded because they had respiratory signs/symptoms on admission on chart review. Also, 65 patients (1.1%) did not have respiratory symptoms. Finally, 55 patients had Ct values available and were included in this analysis. The median age of the final cohort was 56 years and 51% were male. Our assessment revealed that 23 patients (42%) were likely infectious. The median duration of in-hospital isolation was 5 days for those likely infectious and 2 days for those deemed noninfectious.

SARS-CoV-2 was infrequent among patients admitted for reasons unrelated to COVID-19. An assessment of the likelihood of infectiousness using clinical history, RT-PCR Ct values, and serology may help in making the determination to discontinue isolation and conserve resources.

To determine patient-specific risk factors and clinical outcomes associated with contaminated blood cultures.

A single-center, retrospective case-control risk factor and clinical outcome analysis performed on inpatients with blood cultures collected in the emergency department, 2014–2018. Patients with contaminated blood cultures (cases) were compared to patients with negative blood cultures (controls).

A 509-bed tertiary-care university hospital.

Risk factors independently associated with blood-culture contamination were determined using multivariable logistic regression. The impacts of contamination on clinical outcomes were assessed using linear regression, logistic regression, and generalized linear model with γ log link.

Of 13,782 blood cultures, 1,504 (10.9%) true positives were excluded, leaving 1,012 (7.3%) cases and 11,266 (81.7%) controls. The following factors were independently associated with blood-culture contamination: increasing age (adjusted odds ratio [aOR], 1.01; 95% confidence interval [CI], 1.01–1.01), black race (aOR, 1.32; 95% CI, 1.15–1.51), increased body mass index (BMI; aOR, 1.01; 95% CI, 1.00–1.02), chronic obstructive pulmonary disease (aOR, 1.16; 95% CI, 1.02–1.33), paralysis (aOR 1.64; 95% CI, 1.26–2.14) and sepsis plus shock (aOR, 1.26; 95% CI, 1.07–1.49). After controlling for age, race, BMI, and sepsis, blood-culture contamination increased length of stay (LOS; β = 1.24 ± 0.24; P < .0001), length of antibiotic treatment (LOT; β = 1.01 ± 0.20; P < .001), hospital charges (β = 0.22 ± 0.03; P < .0001), acute kidney injury (AKI; aOR, 1.60; 95% CI, 1.40–1.83), echocardiogram orders (aOR, 1.51; 95% CI, 1.30–1.75) and in-hospital mortality (aOR, 1.69; 95% CI, 1.31–2.16).

These unique risk factors identify high-risk individuals for blood-culture contamination. After controlling for confounders, contamination significantly increased LOS, LOT, hospital charges, AKI, echocardiograms, and in-hospital mortality.

To investigate the relationship between the systemic inflammatory response syndrome (SIRS), early antibiotic use, and bacteremia in solid-tumor patients.

We conducted a retrospective observational study of adults with solid tumors admitted to a tertiary-care hospital through the emergency department over a 2-year period. Patients with neutropenic fever, organ transplant, trauma, or cardiopulmonary arrest were excluded.

Rates of SIRS, bacteremia, and early antibiotics (initiation within 8 hours of presentation) were compared using the χ2 and Student t tests. Binomial regression and receiver operator curves were analyzed to assess predictors of bacteremia and early antibiotics.

Early antibiotics were administered in 507 (37%) of 1,344 SIRS-positive cases and 492 (22%) of 2,236 SIRS-negative cases (P < .0001). Of SIRS-positive cases, 70% had blood cultures drawn within 48 hours and 19% were positive; among SIRS negative cases, 35% had cultures and 13% were positive (19% vs 13%; P = .003). Bacteremic cases were more often SIRS positive than nonbacteremic cases (60% vs 50%; P =.003), but they received early antibiotics at similar rates (50% vs 49%, P = .72). Three SIRS components predicted early antibiotics: temperature (OR, 1.7; 95% CI, 1.31–2.29; P = .0001), tachycardia (OR, 1.4; 95% CI, 1.10–1.69; P < .0001), and white blood-cell count (OR, 1.8; 95% CI, 1.56–2.14; P < .0001). Only temperature (OR, 1.6; 95% CI, 1.09–2.41; P = .01) and tachycardia (OR, 1.5; 95% CI, 1.09–2.06; P = .01) predicted bacteremia. SIRS criteria as a composite were poorly predictive of bacteremia (AUC, 0.57).

SIRS criteria are frequently used to determine the need for early antibiotics, but they are poor predictors of bacteremia in solid-tumor patients. More reliable models are needed to guide judicious use of antibiotics in this population.

In 2015, an international outbreak of Mycobacterium chimaera infections among patients undergoing cardiothoracic surgeries was associated with exposure to contaminated LivaNova 3T heater-cooler devices (HCDs). From June 2017 to October 2020, the Centers for Disease Control and Prevention was notified of 18 patients with M. chimaera infections who had undergone cardiothoracic surgeries at 2 hospitals in Kansas (14 patients) and California (4 patients); 17 had exposure to 3T HCDs. Whole-genome sequencing of the clinical and environmental isolates matched the global outbreak strain identified in 2015.

Investigations were conducted at each hospital to determine the cause of ongoing infections. Investigative methods included query of microbiologic records to identify additional cases, medical chart review, observations of operating room setup, HCD use and maintenance practices, and collection of HCD and environmental samples.

Onsite observations identified deviations in the positioning and maintenance of the 3T HCDs from the US Food and Drug Administration (FDA) recommendations and the manufacturer’s updated cleaning and disinfection protocols. Additionally, most 3T HCDs had not undergone the recommended vacuum and sealing upgrades by the manufacturer to decrease the dispersal of M. chimaera–containing aerosols into the operating room, despite hospital requests to the manufacturer.

These findings highlight the need for continued awareness of the risk of M. chimaera infections associated with 3T HCDs, even if the devices are newly manufactured. Hospitals should maintain vigilance in adhering to FDA recommendations and the manufacturer’s protocols and in identifying patients with potential M. chimaera infections with exposure to these devices.

The spatial and temporal extent of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) environmental contamination has not been precisely defined. We sought to elucidate contamination of different surface types and how contamination changes over time.

We sampled surfaces longitudinally within COVID-19 patient rooms, performed quantitative RT-PCR for the detection of SARS-CoV-2 RNA, and modeled distance, time, and severity of illness on the probability of detecting SARS-CoV-2 using a mixed-effects binomial model.

The probability of detecting SARS-CoV-2 RNA in a patient room did not vary with distance. However, we found that surface type predicted probability of detection, with floors and high-touch surfaces having the highest probability of detection: floors (odds ratio [OR], 67.8; 95% credible interval [CrI], 36.3–131) and high-touch elevated surfaces (OR, 7.39; 95% CrI, 4.31–13.1). Increased surface contamination was observed in room where patients required high-flow oxygen, positive airway pressure, or mechanical ventilation (OR, 1.6; 95% CrI, 1.03–2.53). The probability of elevated surface contamination decayed with prolonged hospitalization, but the probability of floor detection increased with the duration of the local pandemic wave.

Distance from a patient’s bed did not predict SARS-CoV-2 RNA deposition in patient rooms, but surface type, severity of illness, and time from local pandemic wave predicted surface deposition.

To determine the impact of electronic health record (EHR)–based interventions and test restriction on Clostridioides difficile tests (CDTs) and hospital-onset C. difficile infection (HO-CDI).

Quasi-experimental study in 3 hospitals.

957-bed academic (hospital A), 354-bed (hospital B), and 175-bed (hospital C) academic-affiliated community hospitals.

Three EHR-based interventions were sequentially implemented: (1) alert when ordering a CDT if laxatives administered within 24 hours (January 2018); (2) cancellation of CDT orders after 24 hours (October 2018); (3) contextual rule-driven order questions requiring justification when laxative administered or lack of EHR documentation of diarrhea (July 2019). In February 2019, hospital C implemented a gatekeeper intervention requiring approval for all CDTs after hospital day 3. The impact of the interventions on C. difficile testing and HO-CDI rates was estimated using an interrupted time-series analysis.

C. difficile testing was already declining in the preintervention period (annual change in incidence rate [IR], 0.79; 95% CI, 0.72–0.87) and did not decrease further with the EHR interventions. The laxative alert was temporally associated with a trend reduction in HO-CDI (annual change in IR from baseline, 0.85; 95% CI, 0.75–0.96) at hospitals A and B. The gatekeeper intervention at hospital C was associated with level (IRR, 0.50; 95% CI, 0.42-0.60) and trend reductions in C. difficile testing (annual change in IR, 0.91; 95% CI, 0.85–0.98) and level (IRR 0.42; 95% CI, 0.22–0.81) and trend reductions in HO-CDI (annual change in IR, 0.68; 95% CI, 0.50–0.92) relative to the baseline period.

Test restriction was more effective than EHR-based clinical decision support to reduce C. difficile testing in our 3-hospital system.

Hospitals are required to have antibiotic stewardship programs (ASPs), but there are few models for implementing ASPs without the support of an infectious disease (ID) specialist, defined as an ID physician and/or ID pharmacist.

In this study, we sought to understand ASP implementation at hospitals that lack on-site ID support within the Veterans’ Health Administration (VHA).

Using a mandatory VHA survey, we identified acute-care hospitals that lacked an on-site ID specialist. We conducted semistructured interviews with personnel involved in ASP activities.

The study was conducted across 7 VHA hospitals.

In total, 42 hospital personnel were enrolled in the study.

The primary responsibility for ASPs fell on the pharmacist champions, who were typically assigned multiple other non-ASP responsibilities. The pharmacist champions were more successful at gaining buy-in when they had established rapport with clinicians, but at some sites, the use of contract physicians and frequent staff turnover were potential barriers. Some sites felt that having access to an off-site ID specialist was important for overcoming institutional barriers and improving the acceptance of their stewardship recommendations. In general, stewardship champions struggled to mobilize institutional resources, which made it difficult to advance their programmatic goals.

In this study of 7 hospitals without on-site ID support, we found that ASPs are largely a pharmacy-driven process. Remote ID support, if available, was seen as helpful for implementing stewardship interventions. These findings may inform the future implementation of ASPs in settings lacking local ID expertise.

To determine the impact of the coronavirus disease 2019 (COVID-19) pandemic on healthcare-associated infection (HAI) incidence in US hospitals, national- and state-level standardized infection ratios (SIRs) were calculated for each quarter in 2020 and compared to those from 2019.

Central–line–associated bloodstream infections (CLABSIs), catheter-associated urinary tract infections (CAUTIs), ventilator-associated events (VAEs), select surgical site infections, and Clostridioides difficile and methicillin-resistant Staphylococcus aureus (MRSA) bacteremia laboratory-identified events reported to the National Healthcare Safety Network for 2019 and 2020 by acute-care hospitals were analyzed. SIRs were calculated for each HAI and quarter by dividing the number of reported infections by the number of predicted infections, calculated using 2015 national baseline data. Percentage changes between 2019 and 2020 SIRs were calculated. Supporting analyses, such as an assessment of device utilization in 2020 compared to 2019, were also performed.

Significant increases in the national SIRs for CLABSI, CAUTI, VAE, and MRSA bacteremia were observed in 2020. Changes in the SIR varied by quarter and state. The largest increase was observed for CLABSI, and significant increases in VAE incidence and ventilator utilization were seen across all 4 quarters of 2020.

This report provides a national view of the increases in HAI incidence in 2020. These data highlight the need to return to conventional infection prevention and control practices and build resiliency in these programs to withstand future pandemics.

To understand how the different data collections methods of the Alberta Health Services Infection Prevention and Control Program (IPC) and the National Surgical Quality Improvement Program (NSQIP) are affecting reported rates of surgical site infections (SSIs) following total hip replacements (THRs) and total knee replacements (TKRs).

Retrospective cohort study.

Four hospitals in Alberta, Canada.

Those with THR or TKR surgeries between September 1, 2015, and March 31, 2018.

Demographic information, complex SSIs reported by IPC and NSQIP were compared and then IPC and NSQIP data were matched with percent agreement and Cohen’s κ calculated. Statistical analysis was performed for age, gender and complex SSIs. A P value <.05 was considered significant.

In total, 7,549 IPC and 2,037 NSQIP patients were compared. The complex SSI rate for NSQIP was higher compared to IPC (THR: 1.19 vs 0.68 [P = .147]; TKR: 0.92 vs 0.80 [P = .682]). After matching, 7 SSIs were identified by both IPC and NSQIP; 3 were identified only by IPC, and 12 were identified only by NSQIP (positive agreement, 0.48; negative agreement, 1.0; κ = 0.48).

Different approaches to monitor SSIs may lead to different results and trending patterns. NSQIP reports total SSI rates that are consistently higher than IPC. If systems are compared at any point in time, confidence on the data may be eroded. Stakeholders need to be aware of these variations and education provided to facilitate an understanding of differences and a consistent approach to SSI surveillance monitoring over time.

The Canadian Nosocomial Infection Surveillance Program conducted point-prevalence surveys in acute-care hospitals in 2002, 2009, and 2017 to identify trends in antimicrobial use.

Eligible inpatients were identified from a 24-hour period in February of each survey year. Patients were eligible (1) if they were admitted for ≥48 hours or (2) if they had been admitted to the hospital within a month. Chart reviews were conducted. We calculated the prevalence of antimicrobial use as follows: patients receiving ≥1 antimicrobial during survey period per number of patients surveyed × 100%.

In each survey, 28−47 hospitals participated. In 2002, 2,460 (36.5%; 95% CI, 35.3%−37.6%) of 6,747 surveyed patients received ≥1 antimicrobial. In 2009, 3,566 (40.1%, 95% CI, 39.0%−41.1%) of 8,902 patients received ≥1 antimicrobial. In 2017, 3,936 (39.6%, 95% CI, 38.7%−40.6%) of 9,929 patients received ≥1 antimicrobial. Among patients who received ≥1 antimicrobial, penicillin use increased 36.8% between 2002 and 2017, and third-generation cephalosporin use increased from 13.9% to 18.1% (P < .0001). Between 2002 and 2017, fluoroquinolone use decreased from 25.7% to 16.3% (P < .0001) and clindamycin use decreased from 25.7% to 16.3% (P < .0001) among patients who received ≥1 antimicrobial. Aminoglycoside use decreased from 8.8% to 2.4% (P < .0001) and metronidazole use decreased from 18.1% to 9.4% (P < .0001). Carbapenem use increased from 3.9% in 2002 to 6.1% in 2009 (P < .0001) and increased by 4.8% between 2009 and 2017 (P = .60).

The prevalence of antimicrobial use increased between 2002 and 2009 and then stabilized between 2009 and 2017. These data provide important information for antimicrobial stewardship programs.

To describe risk factors associated with inappropriate antibiotic prescribing to children.

Cross-sectional, retrospective analysis of antibiotic prescribing to children, using Kentucky Medicaid medical and pharmacy claims data, 2017.

Population-based sample of pediatric Medicaid patients and providers.

Antibiotic prescriptions were identified from pharmacy claims and used to describe patient and provider characteristics. Associated medical claims were identified and linked to assign diagnoses. An existing classification scheme was applied to determine appropriateness of antibiotic prescriptions.

Overall, 10,787 providers wrote 779,813 antibiotic prescriptions for 328,515 children insured by Kentucky Medicaid in 2017. Moreover, 154,546 (19.8%) of these antibiotic prescriptions were appropriate, 358,026 (45.9%) were potentially appropriate, 163,654 (21.0%) were inappropriate, and 103,587 (13.3%) were not associated with a diagnosis. Half of all providers wrote 12 prescriptions or less to Medicaid children. The following child characteristics were associated with inappropriate antibiotic prescribing: residence in a rural area (odds ratio [OR], 1.09; 95% confidence interval [CI], 1.07–1.1), having a visit with an inappropriate prescriber (OR, 4.15; 95% CI, 4.1–4.2), age 0–2 years (OR, 1.39; 95% CI, 1.37–1.41), and presence of a chronic condition (OR, 1.31; 95% CI, 1.28–1.33).

Inappropriate antibiotic prescribing to Kentucky Medicaid children is common. Provider and patient characteristics associated with inappropriate prescribing differ from those associated with higher volume. Claims data are useful to describe inappropriate use and could be a valuable metric for provider feedback reports. Policies are needed to support analysis and dissemination of antibiotic prescribing reports and should include all provider types and geographic areas.

Alteration of the colonic microbiota following antimicrobial exposure allows colonization by antimicrobial-resistant organisms (AROs). Ingestion of a probiotic, such as Lactobacillus rhamnosus GG (LGG), could prevent colonization or infection with AROs by promoting healthy colonic microbiota. The purpose of this trial was to determine the effect of LGG administration on ARO colonization in hospitalized patients receiving antibiotics.

Prospective, double-blinded, randomized controlled trial of LGG versus placebo among patients receiving broad-spectrum antibiotics.

Tertiary care center.

In total, 88 inpatients receiving broad-spectrum antibiotics were enrolled.

Patients were randomized to receive 1 capsule containing 1×1010 cells of LGG twice daily (n = 44) or placebo (n = 44), stratified by ward type. Stool or rectal-swab specimens were collected for culture at enrollment, during admission, and at discharge. Using selective media, specimens were cultured for Clostridioides difficile, vancomycin-resistant Enterococcus spp (VRE), and antibiotic-resistant gram-negative bacteria. The primary outcome was any ARO acquisition. Secondary outcomes included loss of any ARO if colonized at enrollment, and acquisition or loss of individual ARO.

ARO colonization prevalence at study enrollment was similar (LGG 39% vs placebo 39%). We detected no difference in any ARO acquisition (LGG 30% vs placebo 33%; OR,1.19; 95% CI, 0.38–3.75) nor for any individual ARO acquisition. There was no difference in the loss of any ARO (LGG 18% vs placebo 24%; OR, 1.44; 95% CI, 0.27–7.68) nor for any individual ARO.

LGG administration neither prevented acquisition of ARO nor accelerated loss of ARO colonization.

To estimate the relative risk (RR) of developing methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant Enterococcus (VRE) colonization or infection within 30 days of ambulance transport.

We performed a retrospective cohort study of patients with a principal diagnosis of chest pain presenting to our emergency department (ED) over a 4-year period. Patients were included if they presented from and were discharged to nonhealthcare locations without being admitted. Encounters were stratified by arrival mechanism: ambulance versus private vehicle. We performed propensity score matching and multivariable logistic regression to estimate the RR for the primary outcome.

In total, 321,229 patients had ED encounters during the study period. After applying inclusion criteria and propensity score matching, there were 11,324 patients: 3,903 in the ambulance group and 7,421 in the unexposed group. Among them, 12 patients (0.11%) had the outcome of interest, including 9 (0.08%) with MRSA and 3 (0.03%) with VRE. The 30-day prevalence of MRSA or VRE was larger in the ambulance group than in the unexposed group: 8 (0.20%) and 4 (0.05%), respectively (P = .02). Patients who presented to the ED via ambulance were almost 4 times more likely to have MRSA or VRE within 30 days of their encounter (RR, 3.72; 95% CI, 1.09–12.71; P = .04).

Our cohort study is the first to demonstrate an association between ambulance exposure and pathogen incidence, representing the first step in evaluating medical-transport–associated infection burden to eventually develop interventions to address it.

The objectives of this study were (1) to develop and validate a simulation model to estimate daily probabilities of healthcare-associated infections (HAIs), length of stay (LOS), and mortality using time varying patient- and unit-level factors including staffing adequacy and (2) to examine whether HAI incidence varies with staffing adequacy.

The study was conducted at 2 tertiary- and quaternary-care hospitals, a pediatric acute care hospital, and a community hospital within a single New York City healthcare network.

All patients discharged from 2012 through 2016 (N = 562,435).

We developed a non-Markovian simulation to estimate daily conditional probabilities of bloodstream, urinary tract, surgical site, and Clostridioides difficile infection, pneumonia, length of stay, and mortality. Staffing adequacy was modeled based on total nurse staffing (care supply) and the Nursing Intensity of Care Index (care demand). We compared model performance with logistic regression, and we generated case studies to illustrate daily changes in infection risk. We also described infection incidence by unit-level staffing and patient care demand on the day of infection.

Most model estimates fell within 95% confidence intervals of actual outcomes. The predictive power of the simulation model exceeded that of logistic regression (area under the curve [AUC], 0.852 and 0.816, respectively). HAI incidence was greatest when staffing was lowest and nursing care intensity was highest.

This model has potential clinical utility for identifying modifiable conditions in real time, such as low staffing coupled with high care demand.